![]() ![]() We discussed different problems and solutions of most typical problems. In this article we covered multiple ways to convert JSON data or columns containing JSON data to multiple columns. If we are passing DataFrame then we need to convert it to proper JSON by: data.to_dict() This error may be the result of misuse of the method: pd.json_normalize(). TypeError: string indices must be integers To avoid such errors we might convert the column to string or parse it by library flatten_json: from flatten_json import flatten This error will be raised if we try to apply json.loads to a JSON data: df2.apply(json.loads) To ensure both lists have exactly the same set of elements regardless of order, we can sort both.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |